Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies
if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the
same subfield and year (this is the minimum needed to enter the top 1%, not the average
within it), or reaches the top citation threshold in at least one of its specific research
topics.
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2004500 citationsLi Ding, Tim Finin et al.profile →
Author Peers
Peers are selected by citation overlap in the author's most active subfields.
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This map shows the geographic impact of Li Ding's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Li Ding with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Li Ding more than expected).
This network shows the impact of papers produced by Li Ding. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Li Ding. The network helps show where Li Ding may publish in the future.
Co-authorship network of co-authors of Li Ding
This figure shows the co-authorship network connecting the top 25 collaborators of Li Ding.
A scholar is included among the top collaborators of Li Ding based on the total number of
citations received by their joint publications. Widths of edges
represent the number of papers authors have co-authored together.
Node borders
signify the number of papers an author published with Li Ding. Li Ding is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Ding, Li. (2011). Multiple disaster coupled prediction modeling using multi-agent models. Journal of Tsinghua University(Science and Technology).1 indexed citations
6.
Ding, Li, Dominic DiFranzo, Alvaro Graves, et al.. (2010). Data-gov Wiki: Towards Linking Government Data.. National Conference on Artificial Intelligence.48 indexed citations
7.
Bao, Jie, et al.. (2010). Representing financial reports on the semantic web: a faithful translation from XBRL to OWL. International Semantic Web Conference. 144–152.7 indexed citations
8.
Michaelis, James, Li Ding, & Deborah L. McGuinness. (2009). Towards the Explanation of Workflows.. 60–71.1 indexed citations
9.
Michaelis, James, Li Ding, & Deborah L. McGuinness. (2008). The TW wine agent: a social semantic web demo. International Semantic Web Conference. 153–154.1 indexed citations
10.
Ding, Li, et al.. (2008). Characterizing and Detecting Integrity Issues in OWL Instance Data..4 indexed citations
11.
Silva, Paulo Pinheiro da, et al.. (2008). Presenting TSTP Proofs with Inference Web Tools.. 373. 81–93.4 indexed citations
12.
McGuinness, Deborah L., Peter Fox, Stephan Zednik, et al.. (2008). Annotating and embedding provenance in science data repositories to enable next generation science applications. AGU Fall Meeting Abstracts. 2008.6 indexed citations
13.
Bao, Jie, Li Ding, Deborah L. McGuinness, & James Hendler. (2008). Towards social webtops using semantic wiki. International Semantic Web Conference. 167–168.
14.
Michaelis, James, et al.. (2008). Towards Usable and Interoperable Workflow Provenance: Empirical Case Studies using PML. International Semantic Web Conference. 23–28.2 indexed citations
15.
McGuinness, Deborah L., et al.. (2007). PML 2: A Modular Explanation Interlingua.. 49–55.35 indexed citations
16.
Ding, Li. (2007). Reconstruction of BLP model based on secure subject access. Journal of Communications.
Finin, Tim, et al.. (2003). Using Semantic Web technology in Multi-Agent systems: a case study in the TAGA Trading agent environment.9 indexed citations
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive
bibliographic database. While OpenAlex provides broad and valuable coverage of the global
research landscape, it—like all bibliographic datasets—has inherent limitations. These include
incomplete records, variations in author disambiguation, differences in journal indexing, and
delays in data updates. As a result, some metrics and network relationships displayed in
Rankless may not fully capture the entirety of a scholar's output or impact.